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RL Games: High performance RL library

Papers and related links

Some results on interesting environments

Ant_running Humanoid_running

Allegro_Hand_400 Shadow_Hand_OpenAI

Config file

Implemented in Pytorch:

  • PPO with the support of asymmetric actor-critic variant
  • Support of end-to-end GPU accelerated training pipeline with Isaac Gym and Brax
  • Masked actions support
  • Multi-agent training, decentralized and centralized critic variants
  • Self-play

Implemented in Tensorflow 1.x (not updates now):

  • Rainbow DQN
  • A2C
  • PPO


Clone repo and run: pip install -e .

Or: pip install git+


NVIDIA Isaac Gym

Download and follow the installation instructions from
Run from python/rlgpu directory:

python --task Ant --headless
python --task Ant --play --checkpoint nn/Ant.pth --num_envs 100

python --task Humanoid --headless
python --task Humanoid --play --checkpoint nn/Humanoid.pth --num_envs 100

Shadow Hand block orientation task
python --task ShadowHand --headless
python --task ShadowHand --play --checkpoint nn/ShadowHand.pth --num_envs 100

Atari Pong
python --train --file rl_games/configs/atari/ppo_pong.yaml
python --play --file rl_games/configs/atari/ppo_pong.yaml --checkpoint nn/PongNoFrameskip.pth

Brax Ant
python --train --file rl_games/configs/brax/ppo_ant.yaml
python --play --file rl_games/configs/atari/ppo_ant.yaml --checkpoint nn/Ant_brax.pth


  • Some of the supported envs are not installed with, you need to manually install them

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